R Markdown PDF Challenge

The following assignment is an exercise for the reproduction of this .html document using the RStudio and RMarkdown tools we’ve shown you in class. Hopefully by the end of this, you won’t feel at all the way this poor PhD student does. We’re here to help, and when it comes to R, the internet is a really valuable resource. This open-source program has all kinds of tutorials online.

http://phdcomics.com/ Comic posted 1-17-2018

Challenge Goals

The goal of this R Markdown html challenge is to give you an opportunity to play with a bunch of different RMarkdown formatting. Consider it a chance to flex your RMarkdown muscles. Your goal is to write your own RMarkdown that rebuilds this html document as close to the original as possible. So, yes, this means you get to copy my irreverant tone exactly in your own Markdowns. It’s a little window into my psyche. Enjoy =)

hint: go to the PhD Comics website to see if you can find the image above
If you can’t find that exact image, just find a comparable image from the PhD Comics website and include it in your markdown

Here’s a header!

Let’s be honest, this header is a little arbitrary. But show me that you can reproduce headers with different levels please. This is a level 3 header, for your reference (you can most easily tell this from the table of contents).

Another header, now with maths

Perhaps you’re already really confused by the whole markdown thing. Maybe you’re so confused that you’ve forgotton how to add. Never fear! ~~A calculator~~ R is here:

1231521+12341556280987

## [1] 1.234156e+13

Table Time

Or maybe, after you’ve added those numbers, you feel like it’s about time for a table! I’m going to leave all the guts of the coding here so you can see how libraries (R packages) are loaded into R (more on that later). It’s not terribly pretty, but it hints at how R works and how you will use it in the future. The summary function used below is a nice data exploration function that you may use in the ^future.

library(knitr)
kable(summary(cars),caption="I made this table with kable in the knitr package library")

I made this table with kable in the knitr package library
	speed	dist
	Min. : 4.0	Min. : 2.00
	1st Qu.:12.0	1st Qu.: 26.00
	Median :15.0	Median : 36.00
	Mean :15.4	Mean : 42.98
	3rd Qu.:19.0	3rd Qu.: 56.00
	Max. :25.0	Max. :120.00

And now you’ve almost finished your first RMarkdown! Feeling excited? We are! In fact, we’re so excited that maybe we need a big finale eh? Here’s ours! Include a fun gif of your choice!

Origins and Earth Systems

Evidence worksheet 01

The template for the first Evidence Worksheet has been included here. The first thing for any assignment should link(s) to any relevant literature (which should be included as full citations in a module references section below).

You can copy-paste in the answers you recorded when working through the evidence worksheet into this portfolio template.

As you include Evidence worksheets and Problem sets in the future, ensure that you delineate Questions/Learning Objectives/etc. by using headers that are 4th level and greater. This will still create header markings when you render (knit) the document, but will exclude these levels from the Table of Contents. That’s a good thing. You don’t’ want to clutter the Table of Contents too much.

Whitman et al 1998

Learning objectives

Describe the numerical abundance of microbial life in relation to ecology and biogeochemistry of Earth systems.

General questions

What were the main questions being asked?
What amount of carbon mass and nutrients are containted in all the prokaryotes on Earth, and what is the total abundance of prokaryotes globally?
Which environments are significant contributers of prokaryotic biomass and which one is the most important?
How can all of these factors actually be measured?
How can we estimate the uncertainty of said measurements?
What effect does the global microbial population have on biogeochemistry?
What were the primary methodological approaches used?
Available numbers were taken from studies from each small environment. They were converted to the same format and units, then averaged for each environment. Each averaged measurement of an environment was extrapolated to be proportionate to the size of said environment. Then they had to do a fair amount of guesstimation, combined with comparisons to older values to see if their results were within a reasonable order of magnitude. They also calculated the results of sections by different methods to see if all gave the same order of magnitude.
Summarize the main results or findings.
Nearl all prokaryotic life comes from three main environments: aquatic environments, the subsurface, and soil. About half of the global organic C is contained in microbial cells and 90% of global nutrients. This is 10x the nutrients contained in plants globally. They also determined the turnover rate of cells in each environment.
Do new questions arise from the results
How likely is their calculated turnver time of thousands of years in the subsurface to be accurate? (Dr Hallam says pretty likely)
Where does energy for life in the subsurface come from? (Dr Hallam says there isn’t much in total, but what little there is comes from metal reduction)
Would the averages for each environment change if more measurements were taken in certain places?
Is the biogeochemical effect in the subsurface large, even if the turnover rate, and therefore microbial activity, is so slow?
Were there any specific challenges or advantages in understanding the paper (e.g. did the authors provide sufficient background information to understand experimental logic, were methods explained adequately, were any specific assumptions made, were conclusions justified based on the evidence, were the figures or tables useful and easy to understand)?
I think there were a lot of necessary assumptions made to reach their conclusions, but the reason for each assumption was made clear so I was able to follow the logic of how they reached their conclusions pretty well.

Evidence worksheet 02

Problem set 01

Learning objectives:

Describe the numerical abundance of microbial life in relation to the ecology and biogeochemistry of Earth systems.

Specific questions:

What are the primary prokaryotic habitats on Earth and how do they vary with respect to their capacity to support life? Provide a breakdown of total cell abundance for each primary habitat from the tables provided in the text.
Aquatic - The majority of prokaryotic life is found in the open ocean. They have a short turnover time and therefore a high cellular productivity, which means that mutations and other rare genetic events are most likely to occur here than other habitats. Total abundance: \[1180*10^26\]
Total abundance: 255.6 x 10^27
Subsurface - Major habitat for prokaryotes, with most of the subsurface biomass supported by organic matter deposited from the surface. Total abundance: 3.8 x 10^30
What is the estimated prokaryotic cell abundance in the upper 200 m of the ocean and what fraction of this biomass is represented by marine cyanobacterium including Prochlorococcus? What is the significance of this ratio with respect to carbon cycling in the ocean and the atmospheric composition of the Earth?
What is the difference between an autotroph, heterotroph, and a lithotroph based on information provided in the text?
Based on information provided in the text and your knowledge of geography what is the deepest habitat capable of supporting prokaryotic life? What is the primary limiting factor at this depth?
Based on information provided in the text your knowledge of geography what is the highest habitat capable of supporting prokaryotic life? What is the primary limiting factor at this height?
Based on estimates of prokaryotic habitat limitation, what is the vertical distance of the Earth’s biosphere measured in km?
How was annual cellular production of prokaryotes described in Table 7 column four determined? (Provide an example of the calculation)
What is the relationship between carbon content, carbon assimilation efficiency and turnover rates in the upper 200m of the ocean? Why does this vary with depth in the ocean and between terrestrial and marine habitats?
How were the frequency numbers for four simultaneous mutations in shared genes determined for marine heterotrophs and marine autotrophs given an average mutation rate of 4 x 10^-7 per DNA replication? (Provide an example of the calculation with units. Hint: cell and generation cancel out)
Given the large population size and high mutation rate of prokaryotic cells, what are the implications with respect to genetic diversity and adaptive potential? Are point mutations the only way in which microbial genomes diversify and adapt?
What relationships can be inferred between prokaryotic abundance, diversity, and metabolic potential based on the information provided in the text?

Module 01 references

Utilize this space to include a bibliography of any literature you want associated with this module. We recommend keeping this as the final header under each module.

An example for Whitman and Wiebe (1998) has been included below.

Whitman WB, Coleman DC, and Wiebe WJ. 1998. Prokaryotes: The unseen majority. Proc Natl Acad Sci USA. 95(12):6578–6583. PMC33863

MICB425 Portfolio

Jack Anthony 25067142

version: March 20, 2018

Module 01

Module 01 portfolio check

Data science Friday

Installation check

Portfolio repo setup

RMarkdown pretty PDF challenge